A quantitative analysis of subsidence produces curves for subsidence and sediment accumulation rates through time, which are useful to understand the tectonic mechanisms of basin subsidence and evolution. However, data for subsidence study are scattered and sparse in a huge time and dimensional space. Therefore, to analyze subsidence of extensive area, the data have to be interpolated by modelling technique. Modelling is a highly efficient way to figure out the stratigraphic context, structure, and subsidence of sedimentary basins by showing how geological data are distributed over the area. However, several obstacles usually emerge during the process of 3D modelling of sedimentary basins. The main problem is to combine geologic data and 3D modelling methods. In order to allow geologists to analyze and model data easily, this study uses MATLAB which is an extensive and widely used numerical computing environment. We focus on developing a MATLAB program for analyzing and 3D modelling subsidence of a sedimentary basin.
This program consists of mainly three steps; 1) data input, 2) subsidence analysis, and 3) 3D modelling. For analyzing and modelling the subsidence we arranged sample borehole data to a set of 3D points based on their map location (x, y coordinates) and the depths (z1, z2, z3, …) of stratigraphic boundaries and the subsided basement. Subsidence was analyzed by using the backstripping equations and additional data provided from boreholes and references. The process resulted in 3D Surface visualizations of the total basement subsidence and the tectonic subsidence.
The reconstruction of subsidence maps from the arranged data used the Thin-Plate Spline (TPS) which can be employed to reconstruct a smooth surface from a set of 3D points. The basic physical model of the TPS is based on the bending behavior of a thin metal sheet that is constrained only by a sparse set of fixed points. MATLAB was used to calculate the TPS interpolation function. Our program evaluates the TPS interpolation function at intersection points of a grid on the xy-plane. An adjustable resolution of the grid ensures that all details of the surface are captured. The final surface is obtained by linear interpolation between the grid points. The reconstructed surface can be viewed as solid area or contour plot. A colormap is used to encode the depth of the surface in order to emphasize its shape. This program is still under development and other interpolation methods will be tested, in order to increase its usability and accuracy.
The major functions of this program are illustrated by a case study from a 35x62 km area located in the Neogene Vienna Basin. The studied data were mainly derived from about 100 boreholes drilled in the area. The stratigraphic column and age range were divided into six stages based on the Central Paratethys Stages in the Miocene. At each stage, visualizations of the total basement subsidence and the tectonic subsidence were generated in this study. Within the case study, our software tool allowed us to gain better insight into the data and for the tectonic evolution of the Vienna Basin. However, the modelling approach currently cannot integrate the displacement and timing of faults completely. It therefore gives partly fuzzy, non-complete pictures contouring over faults. In addition, different faulting (timing of fault movement) may have caused differences in sedimentation, subsidence, and their rates in different areas through time.